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Detection of Stylometric Writeprint from the Turkish Texts

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dc.contributor.author Canbay, Pelin
dc.contributor.author Sezer, Ebru Akçapınar
dc.contributor.author Sever, Hayri
dc.date.accessioned 2022-04-01T12:13:27Z
dc.date.available 2022-04-01T12:13:27Z
dc.date.issued 2020
dc.identifier.citation Canbay, Pelin; Sezer, Ebru Akçapınar; Sever, Hayri (2020). "Detection of Stylometric Writeprint from the Turkish Texts", 28th Signal Processing and Communications Applications Conference (SIU). tr_TR
dc.identifier.uri http://hdl.handle.net/20.500.12416/5247
dc.description.abstract Authorship attribution studies aim to extract information about the author by analyzing the data in the text form. With the increase of anonymous authors in digital environments, the need for these works is increasing day by day. Although there exists lots of studies focuse on stylometric writeprint detection in different languages using different attributes, there is no standard feature set and detection algorithm to be evaluated in these studies. Giving priority to Turkish texts, in this study, which features are more distinctive for determining stylistic writeprint of text, and which methods will contribute to increase the success to be achieved are shown with experimental studies. tr_TR
dc.language.iso eng tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Stylometric Analysis tr_TR
dc.subject Authorship Attribution tr_TR
dc.subject Writeprint Detection tr_TR
dc.title Detection of Stylometric Writeprint from the Turkish Texts tr_TR
dc.type conferenceObject tr_TR
dc.relation.journal 28th Signal Processing and Communications Applications Conference (SIU) tr_TR
dc.contributor.authorID 11916 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Yazılım Mühendisliği Bölümü tr_TR


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